A pilot study of circulating miRNAs as potential biomarkers of early stage breast cancer

Abstract

Background: To date, there are no highly sensitive and specific minimally invasive biomarkers for detection of breast cancer at an early stage. The occurrence of circulating microRNAs (miRNAs) in blood components (including serum and plasma) has been repeatedly observed in cancer patients as well as healthy controls. Because of the significance of miRNA in carcinogenesis, circulating miRNAs in blood may be unique biomarkers for early and minimally invasive diagnosis of human cancers. The objective of this pilot study was to discover a panel of circulating miRNAs as potential novel breast cancer biomarkers.

Methodology/principal findings: Using microarray-based expression profiling followed by Real-Time quantitative Polymerase Cycle Reaction (RT-qPCR) validation, we compared the levels of circulating miRNAs in plasma samples from 20 women with early stage breast cancer (10 Caucasian American (CA) and 10 African American (AA)) and 20 matched healthy controls (10 CAs and 10 AAs). Using the significance level of p<0.05 constrained by at least two-fold expression change as selection criteria, we found that 31 miRNAs were differentially expressed in CA study subjects (17 up and 14 down) and 18 miRNAs were differentially expressed in AA study subjects (9 up and 9 down). Interestingly, only 2 differentially expressed miRNAs overlapped between CA and AA study subjects. Using receiver operational curve (ROC) analysis, we show that not only up-regulated but also down-regulated miRNAs can discriminate patients with breast cancer from healthy controls with reasonable sensitivity and specificity. To further explore the potential roles of these circulating miRNAs in breast carcinogenesis, we applied pathway-based bioinformatics exploratory analysis and predicted a number of significantly enriched pathways which are predicted to be regulated by these circulating miRNAs, most of which are involved in critical cell functions, cancer development and progression.

Conclusions: Our observations from this pilot study suggest that the altered levels of circulating miRNAs might have great potential to serve as novel, noninvasive biomarkers for early detection of breast cancer.

Figure 1. Characteristics of differentially expressed microRNAs (P<0.05 & FC >2) obtained from the case-versus-control comparison using all 40 participants.

A–B) Hierarchical clustering and principal component clustering of differentially expressed microRNAs C) The overlap of differentially expressed microRNAs obtained from all 40 participants with those from AA group only (20 participants) and CA group only (20 participants), respectively.

Figure 2. Characteristics of differentially expressed microRNAs (P<0.05 & FC >2) obtained from the case-versus-control comparison.

A–B) Hierarchical clustering and principal component clustering of miRNAs in samples from AA participants. D–E) Hierarchical clustering and principal component clustering of miRNAs in samples from CA participants. C, F) The distribution of novel vs. known differentially expressed miRNAs obtained from AA group and CA group, separately.

Figure 3. Venn diagrams showing the overlap at microRNA, target gene and pathway levels, respectively.

A) The differentially expressed microRNAs (P<0.05 & FC >2). B) The target genes predicted to be regulated by differentially expressed microRNAs. C) The enriched pathways (P<0.01) in target genes predicted to be regulated by differentially expressed microRNAs.

Figure 4. Decreased plasma levels of let-7c for patients with breast cancer versus healthy controls in CA group.

A–B) Data from microarray profiling of 20 participants: The fold change of let-7c in case relative to control is −3.0 (P = 0.015, AUC  = 0.84). C–D) Data from RT-qPCR validation in an independent set of 30 participants: The fold change of let-7c in case relative to control is −1.9 (P = 0.01, AUC  = 0.78).

Figure 5. Increased plasma levels of miR-589 for patients with breast cancer versus healthy controls in CA group.

A–B) Data from microarray profiling of 20 participants: The fold change of miR-589 in case relative to control is 6.9 (P = 0.0131, AUC  = 0.62). C–D) Data from RT-qPCR validation in an independent set of 30 participants: The fold change of miR-589 in case relative to control is 3.3 (P = 0.0009, AUC  = 0.85).

Figure 6. Increased plasma levels of miR-425* for patients with breast cancer versus healthy controls in AA group.

A–B) Data from microarray profiling of 20 participants: The fold change of miR-425* in case relative to control is 5.0 (P = 0.00328, AUC  = 0.79). C–D) Data from RT-qPCR validation in the same 20 participants: The fold change of miR-425* in case relative to control is 3.3 (P = 0.01226, AUC  = 0.83).

Figure 7. Decreased plasma levels of let-7d* for patients with breast cancer versus healthy controls in AA group.

A–B) Data from microarray profiling of 20 participants: The fold change of let-7d* in case relative to control is −6.6 (p = 0.03063, AUC = 0.73). C-D) Data from RT-qPCR validation in the same 20 participants: The fold change of let-7d* in case relative to control is −9.4 (P = 1.6e-7, AUC  = 0.99).